nosql数据库学习之mongodb之group by限制 如果你用group 命令的话可能会遇到下面两种错误： www.2cto.com a.)命令：db.flogsamplelog.group({cond:{datetimes:20111027},key:{pid:1},initial:{count:0},reduce:function(doc,prev){if(doc.pid==prev.pid)prev
nosql数据库学习之mongodb之group by限制
如果你用group 命令的话可能会遇到下面两种错误：
  www.2cto.com  
a.)命令：db.flogsamplelog.group({cond:{datetimes:20111027},key:{pid:1},initial:{count:0},reduce:function(doc,prev){if(doc.pid==prev.pid)prev.count++;}})
error:
mon oct 31 12:00:00uncaught exception: group command failed: { 
errmsg : exception: group() can't handle more than 10000 unique keys, 
code : 10043, 
ok : 0 
} 直接访问shard server端口
b.)命令：db.flogsamplelog.group({cond:{pid:322963713,datetimes:20111027},key:{worktype:1},initial:{count:0},reduce:function(doc,prev){if(doc.worktype==prev.worktype)prev.count++;}})
error：
mon oct 31 12:00:09 uncaught exception: group command failed: { ok : 0, errmsg : can't do command: group on sharded collection } 直接访问route server端口
其次我们在mongodb权威指南上也能发现这样的语句:
the price of using mapreduce is speed: group is not particularly speedy, but
mapreduce is slower and is not supposed to be used in “real time.” you run
mapreduce as a background job, it creates a collection of results, and then 
you can query that collection in real time.
经过测试发现group by效率在建立索引之后也没有实质性提高。
具体命令中涉及到的字段以及表定义，这里就不在敷衍。